Literature DB >> 31781750

Forecasting the 2014 West African Ebola Outbreak.

Cristina Carias, Justin J O'Hagan, Manoj Gambhir, Emily B Kahn, David L Swerdlow, Martin I Meltzer.   

Abstract

In 2014-2015, a large Ebola outbreak afflicted Liberia, Guinea, and Sierra Leone. We performed a systematic review of 26 manuscripts, published between 2014 and April 2015, that forecasted the West African Ebola outbreak while it was occurring, and we derived implications for how results could be interpreted by policymakers. Forecasted case counts varied widely. An important determinant of forecast accuracy for case counts was how far into the future predictions were made. Generally, forecasts for less than 2 months into the future tended to be more accurate than those made for more than 10 weeks into the future. The exceptions were parsimonious statistical models in which the decay of the rate of spread of the pathogen among susceptible individuals was dealt with explicitly. The most important lessons for policymakers regarding future outbreaks, when using similar modeling results, are: 1) uncertainty of forecasts will be greater in the beginning of the outbreak; 2) when data are limited, forecasts produced by models designed to inform specific decisions should be used complementarily for robust decision-making (e.g., 2 statistical models produced the most reliable case-counts forecasts for the studied Ebola outbreak but did not enable understanding of interventions' impact, whereas several compartmental models could estimate interventions' impact but required unavailable data); and 3) timely collection of essential data is necessary for optimal model use. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2020. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Entities:  

Keywords:  Ebola viral disease; West Africa; forecast; infectious disease models

Mesh:

Year:  2019        PMID: 31781750     DOI: 10.1093/epirev/mxz013

Source DB:  PubMed          Journal:  Epidemiol Rev        ISSN: 0193-936X            Impact factor:   6.222


  2 in total

1.  Forecasting efforts from prior epidemics and COVID-19 predictions.

Authors:  Pranay Nadella; Akshay Swaminathan; S V Subramanian
Journal:  Eur J Epidemiol       Date:  2020-07-17       Impact factor: 8.082

2.  Multi-model forecasts of the ongoing Ebola epidemic in the Democratic Republic of Congo, March-October 2019.

Authors:  Kimberlyn Roosa; Amna Tariq; Ping Yan; James M Hyman; Gerardo Chowell
Journal:  J R Soc Interface       Date:  2020-08-26       Impact factor: 4.118

  2 in total

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